Advanced Solid TumorNCT06432283
A Machine Learning-based Estimated Survival Model
An observational study of Advanced Solid Tumor, run by Zhao Siyao at 1 site in China.
Trial summary
Malignant tumors are the leading cause of death in elderly patients, and palliative care can improve the quality of life for elderly advanced cancer patients. One of the main reasons why these patients are not included in palliative care is the lack of accurate estimation of their survival period by patients, family… Read more about this study
- Who is it for?
- Ages 60 years and older
- Conditions the study is for
- Advanced Solid Tumor
- Type of treatment
- Injection or infusion
- How many people
- 1,000 participants
- Where
- 1 siteChina
- Study dates
- 1 May 2024to 31 Dec 2026
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 60 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: Advanced cancer （stage III and IV） malignant tumor patients aged 60 years and above.
Who may be able to join
None listed.
Who cannot join
- Patients who refuse to participate in the study;
- Patients who, for various reasons, are unable to cooperate and complete the questionnaire survey;
- Patients who, for various reasons, are unable to cooperate and complete the follow-up.
Trial locations and contacts
1 site in 1 country.
About this study
Official title: Construction and Validation of a Machine Learning-based Estimated Survival Model for Elderly Patients With Advanced Malignancy
Malignant tumors are the leading cause of death in elderly patients, and palliative care can improve the quality of life for elderly advanced cancer patients. One of the main reasons why these patients are not included in palliative care is the lack of accurate estimation of their survival period by patients, family members, and doctors. Both doctors and patients tend to be overly optimistic about the survival period of elderly advanced cancer patients, leading to overtreatment. Therefore, assessing the risk of death for these patients and further establishing a survival period estimation model can improve the accuracy of doctors' clinical predictions of patient survival, facilitate early referral to palliative care, and promote rationalization of medical decision-making.
Read the detailed description
- By searching the literature, conducting systematic reviews, and meta-analyses, we aim to uncover the prognostic factors related to death in elderly advanced cancer patients.
- Based on evidence-based data and considering the clinical conditions of elderly advanced cancer patients in China, we will establish relevant entries for a risk assessment scale for death in elderly advanced cancer patients. By using the Delphi expert consultation evaluation method, we will finalize the assessment scale framework, laying the theoretical foundation for the establishment and validation of a death risk prediction model for elderly advanced cancer patients in China.
- Develop a survival estimation model for elderly advanced cancer patients; through metabolomics studies and other research methods, we will investigate metabolic biomarkers related to predicting the survival period of elderly advanced cancer patients.
- Conditions
- Advanced Solid Tumor
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
| Study group | Role | What they receive |
|---|---|---|
| advanced cancer (stage III and IV) patients aged 60 years and above. | advanced cancer (stage III and IV) patients aged 60 years and above who are receiving treatment at the mentioned institution. The research subjects voluntarily participate and sign informed consent forms. |
What is being measured
The primary outcome is the main question the study is designed to answer.
A model
Build a survival estimation model for elderly late-stage cancer patients.
Measured: 2026-12-31
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted29 May 2024
- Study start1 May 2024
- Primary completion31 Dec 2025 (estimated)
- Study completion31 Dec 2026 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Advanced Solid TumorStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 1,000 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Zhao Siyao
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor-investigator, Zhao Siyao, West China Hospital
- Investigators
- Siyao Zhao, postgraduate, Principal investigator, West China Hospital
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06432283
- Sponsor's protocol ID
- 2024 Review (807)
- Status last verified
- May 2024
- First submitted
- 15 May 2024
- Last updated
- 29 May 2024
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
Study at a glance
From the registry record, last updated by the sponsor on 29 May 2024. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Construction and Validation of a Machine Learning-based Estimated Survival Model for Elderly Patients With Advanced Malignancy
- ClinicalTrials.gov ID
- NCT06432283
- Acronym / sponsor ID
- 2024 Review (807)
- Conditions
- Advanced Solid Tumor
- Study type
- Observational
- Recruitment status
- Active, not recruiting
- Enrolment
- 1,000 participants (estimated)
- Lead sponsor
- Zhao SiyaoUniversity, hospital or other
- Study start
- 1 May 2024 (actual)
- Primary completion
- 31 Dec 2025 (estimated)
- Study completion
- 31 Dec 2026 (estimated)
- First posted
- 29 May 2024 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
Malignant tumors are the leading cause of death in elderly patients, and palliative care can improve the quality of life for elderly advanced cancer patients. One of the main reasons why these patients are not included in palliative care is the lack of accurate estimation of their survival period by patients, family members, and doctors. Both doctors and patients tend to be overly optimistic about the survival period of elderly advanced cancer patients, leading to overtreatment. Therefore, assessing the risk of death for these patients and further establishing a survival period estimation model can improve the accuracy of doctors' clinical predictions of patient survival, facilitate early referral to palliative care, and promote rationalization of medical decision-making.
Detailed description
- By searching the literature, conducting systematic reviews, and meta-analyses, we aim to uncover the prognostic factors related to death in elderly advanced cancer patients.
- Based on evidence-based data and considering the clinical conditions of elderly advanced cancer patients in China, we will establish relevant entries for a risk assessment scale for death in elderly advanced cancer patients. By using the Delphi expert consultation evaluation method, we will finalize the assessment scale framework, laying the theoretical foundation for the establishment and validation of a death risk prediction model for elderly advanced cancer patients in China.
- Develop a survival estimation model for elderly advanced cancer patients; through metabolomics studies and other research methods, we will investigate metabolic biomarkers related to predicting the survival period of elderly advanced cancer patients.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| advanced cancer (stage III and IV) patients aged 60 years and above. | – | –advanced cancer (stage III and IV) patients aged 60 years and above who are receiving treatment at the mentioned institution. The research subjects voluntarily participate and sign informed consent forms. |
Who may qualify
- Ages
- 60 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- Advanced cancer （stage III and IV） malignant tumor patients aged 60 years and above.
Key inclusion criteria (0 listed)
Key exclusion criteria (3 listed)
- Patients who refuse to participate in the study;
- Patients who, for various reasons, are unable to cooperate and complete the questionnaire survey;
- Patients who, for various reasons, are unable to cooperate and complete the follow-up.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
A model
Time frame: 2026-12-31
Build a survival estimation model for elderly late-stage cancer patients.
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 29 May 2024.
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RecruitingPhase 2
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Siyao Zhao, postgraduate principal investigator
West China Hospital
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Advanced Solid Tumor, run by Zhao Siyao at 1 site in China.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 0 inclusion and 3 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: under way, not looking for participants, as of the sponsor's last update on 29 May 2024. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in China. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
A model (time frame: 2026-12-31). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 29 May 2024.